In this post I would like to specifically discuss the assertion that "There are no epidemiological studies investigating potential effects of GM food consumption on human health."

To
those unfamiliar with modern crop science and genetics, that could
sound like a very condemning statement. But that begs the question, have
there been epidemiological studies investigating the potential effects
of conventionally and mutagenically improved crops on human health?

Its
also a true statement that there are no epidemiological studies
investigating the relative safety of using the stairs vs. elevators vs.
escalators vs. leaping out the top floor window with regard to human
health. (although I am sure actuaries have assessed property/casualty
probabilities associated with similar kinds of risks related to building
design, we don't have people losing sleep over lack of publication in
this area)These
last examples might seem extreme and unrelated, but they illustrate the
point that for some things, conducting an expensive (and difficult)
epidemiological study to assess impacts on human health makes little
practical sense.

What reasoning
would make us think this is necessary for genetically modified foods?
If we were discussing inclusion of traits known to impact metabolism or
hormone levels or some other biological function this might make sense.
But the types of crops approved for human consumption don't have traits
known to behave this way. Some critics might assert that it is the
unknown consequences (changes in DNA, changes in proteins, or
metabolism) that we should be worried about.

However,
scientists know that these kinds of genetic disruptions are not any
more proliferate with genetically engineered crops than those related to
traditional and mutagenic crop improvement that have been consumed and
accepted by consumers without question for hundreds (thousands) of years
or more in some cases and decades in others. They are substantially
equivalent in this regard.It
turns out that the statement about the absence of epidemiological
studies is really irrelevant when it comes to assessing the risks
associated with genetically engineered food consumption. Arguments using
epidemiological studies to form a psychological baseline or frame of reference are
akin to strawman statements that could raise unnecessary doubts and
fears about a technology that actually exhibits characteristics beneficial to human health and the environment. References:

This was the first time I had seen this paper so I spent some time going through it to see what kinds of arguments were being made. Below are a few excerpts and some discussion.

"the scarcity and contradictory nature of the scientific evidence published to date prevents conclusive claims of safety, or of lack of safety, of GMOs. Claims of consensus on the safety of GMOs are not supported by an objective analysis of the refereed literature."

"The health, environment, and agriculture authorities of most nations recognize publicly that no blanket statement about the safety of all GMOs is possible and that they must be assessed on a 'case-by-case' basis."

"an expert panel of the Royal Society of Canada issued a report that was highly critical of the regulatory system for GM foods and crops in that country. The report declared that it is 'scientifically unjustifiable' to presume that GM foods are safe without rigorous scientific testing and that the 'default prediction' for every GM food should be that the introduction of a new gene will cause 'unanticipated changes' in the expression of other genes, the pattern of proteins produced, and/or metabolic activities."

"We support the application of the Precautionary Principle with regard to the release and transboundary movement of GM crops and foods."

I have not had a chance to check every single reference and citation made. However the general framework sketched out in the paper I am getting is this:

there is no absolute or conclusive evidence that genetically engineered foods are safe or unsafe

“We found that the improvement of a plant variety through the
acquisition of a new desired trait, using either mutagenesis or
transgenesis, may cause stress and thus lead to an altered expression of
untargeted genes. In all of the cases studied, the observed alteration
was more extensive in mutagenized than in transgenic plants” - (Batista, et al; 2008)
With greater disruptions, critics might favor increased regulatory scrutiny. However, we
do not have a framework in place for mutagenically improved crop
varieties that have been safely used for decades and approved by the
organic food industry and accepted by consumers, nor do we have anything like this for conventionally bred crops. If an argument for the precautionary principle holds for genetically engineered crops on this basis, then it should also hold for all types of crop improvement.

Therefore it seems tenuous to make a scientific risk based justification for special treatment of genetically engineered crops without further evidence. When many refer to a consensus on the safety of genetically engineered foods, this is what I have in mind.

Policies related to genetically engineered foods leveraging the precautionary principle could lead to increased risk of doing more harm than good to human health and the environment if policies prevent or delay adoption of traits that could decrease use of toxic pesticides, or reduce carbon emissions and improve soil conservation as some biotech traits have been shown to do in the literature.

Sunday, July 02, 2017

Research from the American Journal of Clinical Nutrition finds no link to obesity and soft drink consumption.

"We showed no association between sugar-sweetenedbeverage consumption, juice consumption, and adolescent weightgain over a 5-y period. A direct association between diet beveragesand weight gain appeared to be explained by dieting practices.Adolescents who consumed little or no white milk gained significantlymore weight than their peers who consumed white milk. Futureresearch that examines beverage habits and weight among adolescentsshould address portion sizes, adolescent maturation, and dieting behaviors."

This corroborates previous findings from the journal Nutrition:

"Our
analysis shows no evidence for an association between SSB consumption
at age 5 or 7 y and fat mass at age 9 y in this cohort of British
children"

A recent blog post (link)
gets close to accurately reporting the issue of high fructose corn
syrup- a sweetener chemically identical to table sugar found in soft
drinks:

"Fructose
and high-fructose corn syrup aren't the same. It appears that the
writer, Lois Rogers, conflated the two and jumped to all kinds of
incorrect conclusions. For example, that the research had anything at
all to do with "the obesity epidemic." It didn't."

"The
environmental site Grist tends to see everything through an ideological
lens, and so is always on the hunt for evidence that high-fructose corn
syrup is somehow more harmful than common sugar"

But then the article starts to get off track in stating:

"It
is cheap (high fructose corn syrup) in large part because of farm
subsidies. As a result, it is ubiquitous and is making a lot of people
fat, diabetic, and prone to heart disease."

Research taking the claim of a connection between obesity and farm policy in a more direct fashion can be found here( from UC Davis).

"'The
culprit here is not corn subsidies; rather,it is sugar policy that has
restricted imports, driven up the U.S. price of sugar, and encouraged
the replacement of sugar with alternative caloric sweeteners...Given
that consumers generally show limited responses to retail food price
changes, eliminating the corn subsidy would reduce corn-based food
consumption by at most 0.2 percent.""

Similarly,
this weak response of consumers to food prices undermines policies that
advocate taxing soft drinks to reduce consumption and obesity. Research
( from the Mercatus Center at George Mason University)
indicates that the taxes required to have any real affect on obesity
would be in the 1200 percent range, and even if taxes eliminated ( in
this case soda) consumption, the impact on obesity would be very small.
The study concludes that "the sensitivity of individuals to changes in
relative food prices is not sufficient to make “fat taxes” a viable tool
to lower obesity."

These campaigns are nothing more
than emotional appeals designed to solicit support for new taxes and
regulations that ultimately undermine the agriculture industry and
family farms.

Monday, June 19, 2017

According to the USDA, "an estimated 12.7 percent of American households were food insecure at
least some time during the year in 2015, meaning they lacked access to
enough food for an active, healthy life for all household members."

Here are a few more notes:

1) 5.0 percent of U.S. households (6.3 million households) had very low food security
2) There were sizable differences by state
3) ~59% used SNAP, WIC, or the national school lunch program in the previous month
4) The median food-secure household spent 27 percent more for food than the typical food-insecure household

Prices Matter

In
a 2013 Applied Economic Perspectives and Policy article, researchers
found a significant impact of local food prices on food insecurity
developing a novel index of local food prices:

“We
find that the average effect of food prices on the probability of food
insecurity is positive and significant: a one-standard deviation
increase in food prices is associated with increases of 2.7, 2.6, and
3.1 percentage points in household, adult, and child food insecurity,
respectively. These marginal effects amount to 5.0%, 5.1%, and 12.4%
increases in the prevalence of food insecurity for SNAP households,
adults, and children, respectively. These results suggest that indexing
SNAP benefits to local food prices could improve the ability of the
program to reduce food insecurity and economic hardship more generally
in areas with high food prices.”

Food Insecurity, SNAP, and Health Outcomes

In
2012, researchers publishing in the Journal of the American Statistical
Association found that SNAP can have positive mitigating effects on the
health of children.

"Under stronger but plausible
assumptions used to address the selection and classification error
problems, we find that commonly cited relationships between SNAP and
poor health outcomes provide a misleading picture about the true impacts
of the program. Our tightest bounds identify favorable impacts of SNAP
on child health."

Gundersen (2015) finds a relationship between food insecurity and health outcomes for children and seniors.

"after confounding risk factors were controlled for, studies found
that food-insecure children are at least twice as likely to report being
in fair or poor health and at least 1.4 times more likely to have
asthma, compared to food-secure children; and food-insecure seniors have
limitations in activities of daily living comparable to those of
food-secure seniors fourteen years older. The Supplemental Nutrition
Assistance Program (SNAP) substantially reduces the prevalence of food
insecurity and thus is critical to reducing negative health outcomes"

What
we can conclude from this research is that prices matter - while
policies that help reduce or subsidize the purchase price of food can
help reduce food insecurity and provide positive outcomes, policies that
increase prices could have the opposite effect.

The above was an interesting study that found that the impacts of spatial distribution of store locations impacted consumption, although there were no price effects.

In their blog post, the authors discuss how they develop a local price index for food bundles and compare prices for areas that are and are not classified as food deserts.

"Our findings suggest that living in a food desert affects the overall
food prices faced by households to a small extent when consumers can
shop within their home census tracts and in contiguous census tracts.
The difference in prices is largely driven by differences in available
variety. As such, while higher food prices are associated with higher
rates of food insecurity, the results of our work suggest that living in
a food desert is unlikely to influence food insecurity to a great
extent"

In their related paper, presented at the 2015 Agricultural and Applied Economics Association and Western Agricultural Economics Association annual meeting you can read more.

References:

Alisha Coleman-Jensen, Matthew P. Rabbitt, Christian A. Gregory, and Anita Singh.
Household Food Security in the United States in 2015, ERR-215, U.S. Department of
Agriculture, Economic Research Service, September 2016.

Can we feed the world sustainably using organic crop production
methods? Several studies have indicated that there is a yield penalty
for organic cropsThe crop yield gap between organic and conventional agriculture. Agricultural SystemsVolume 108, April 2012, Pages 1-9

The
above indicates much of the previous research was based on research
plots, and penalties for organic vs conventional yields could actually
be worse when scaled up to field size production practices.

The
above research indicates there are significant inflows of N, P, K from
conventional sources. For example, many organic production systems may
rely on manure from animals raised or fed conventionally. If these
positive exteranalities were excluded, the increased energy and land
devoted to organic production would reduce its sustainability further.

Often in addition to some calling for increased organic food production, you will hear additional criticisms of commodity or 'monocrop' agriculture. Themes include criticisms of agricultural policies favoring 'industrial' agriculture
at the expense of healthy fruits and vegetables. However, these
criticisms ignore the importance of calorie density and consumption at a
global level. According to the FAO rice, corn, and wheat provide 60% of
the world's energy intake. Costs of production and economies of scale
favor large scale production of these staples over specialty crops like
broccoli and tomatoes when it terms of providing affordable calorie
dense food to a growing population.

An article in The Conversation discusses some of the possible explanations for these findings. Some critics have suggested that the large number of off target mutations could be related to the specific methods used to control the activity of the Cas9 enzyme, which would impact the number of cuts/edits made in the host DNA that occur.

Others have pointed out that there are various flavors of CRISPR, and even temperature can impact enzyme activity and off target impacts, as well as better and worse methods of detection of off target mutations.

When it comes to food crop applications, critics of CRISPR technology, as well as older recombinant DNA technologies have been largely concerned with genetic disruptions. These criticisms imply that genetic disruptions indicate increased risk to consumers. I think a very relevant question in this regard (give or take the Nature Methods paper) is related to the comparative differences in genetic disruptions between CRISPR mediated genetic improvements vs traditional plant breeding methods including mutation breeding (chemical and radiological mutagenesis used in conventional and organic foods).

Given that previous risk management/regulatory reviews and agencies have found little evidence to restrict or highly regulate traditional and mutagenic crop improvement methods, if genetic disruptions for CRISPR mediated crop improvements are comparable the argument for increased scrutiny of CRISPR based crops is weakened. Previous research indicates that genetic disruptions for traditional plant breeding methods are actually greater than what we observe in recombinant DNA methods.

"There are scientists that help define the social reaction to science and the way that scientists need to communicate issues in technology. Dr. Matthew Harsh is an Assistant Professor at the Centre for Engineering Technology at Concordia University in Montreal Canada. The discussion talks about the interface of natural sciences and social sciences, and how discussions can affect policy"

Monday, June 05, 2017

I found an interesting article in Quanta Magazing discussing a 2012 paper in PNAS discussing game theory in the context of evolutionary processes. The article in Quanta is very detailed and nicely written as well as accessible.

This was interesting because in graduate school and other work I am familiar with, the context of games is defined around human-environment
interactions leading to a Nash Equilibrium/prisoner's dilemma situation
where the dominating strategies involve overuse of a given technology
(antibiotics, herbicide resistant crops, insect resistant crops). In
this context the equilibrium strategies create selection pressure which
ultimately lead to insects, weeds, or bacteria that are resistant to the
given technology. However, the Quanta article provides some examples where researchers are using game theory to
describe actual behavior in nature (i.e. fish, monkeys, or the bacteria
themselves). Here is a slice:

"For example, scientists studying antibiotic resistance are using a game theory scenario called the snowdrift game, in which a player always benefits from cooperating. (If you’re stuck in your apartment building after a blizzard, you benefit by shoveling the driveway, but so does everyone else who lives there and doesn’t shovel.) Some bacteria can produce and secrete an enzyme capable of deactivating antibiotic drugs. The enzyme is costly to produce, and lazy bacteria that don’t make it can benefit by using enzymes produced by their more industrious neighbors. In a strict prisoner’s dilemma scenario, the slackers would eventually kill off the producers, harming the entire population. But in the snowdrift game, the producers have greater access to the enzyme, thus improving their fitness, and the two types of bacteria can coexist."

Below is the citation related to the Dyson and Press paper discussed in the Quanta article:

Press, W. H., & Dyson, F. J. (2012). Iterated Prisoner’s Dilemma contains strategies that dominate any evolutionary opponent. Proceedings of the National Academy of Sciences of the United States of America, 109(26), 10409–10413. http://doi.org/10.1073/pnas.1206569109

In graduate school (2005) I worked on an independent studies project exploring the idea of combining population genetics and game theory to model pest resistance to Bt traits in corn. Recently I decided to look at the literature in that space to see what others have been doing in this space. Below are some articles I have found from a quick search:

Press, William H., and Freeman J. Dyson. “Iterated Prisoner’s Dilemma Contains Strategies That Dominate Any Evolutionary Opponent.” Proceedings of the National Academy of Sciences of the United States of America 109.26 (2012): 10409–10413. PMC. Web. 5 June 2017.

Miranowski, J.A., & Lacy, K.M. (2016). When do resistance management practices pay for the farmer and society? The case of Western Corn Rootworm. AgBioForum, 19(2), 173-183. Available on the World Wide Web: http://www.agbioforum.org.

"In fact, the costs of comprehensively genotyping human subjects have
fallen to the point where major funding bodies, even in the social
sciences, are beginning to incorporate genetic and biological markers
into major social surveys. The National Longitudinal Study of Adolescent
Health, the Wisconsin Longitudinal Study, and the Health and Retirement
Survey have launched, or are in the process of launching, datasets with
comprehensively genotyped subjects…These samples contain, or will soon
contain, data on hundreds of thousands of genetic markers for each
individual in the sample as well as, in most cases, basic economic
variables. How, if at all, should economists use and combine molecular
genetic and economic data? What challenges arise when analyzing
genetically informative data?"

About Me

My primary interests are in applied econometrics with applications related to the interrelationships between genomics, nutrition, health, and the environment. I have a quantitative and analytical background in the areas of applied economics and statistical genetics. I leverage my training with experience in machine learning and predictive modeling using SAS, R, and Python to solve problems. I can understand complex research and discuss the application with a scientist, sales representative, or the customer whose problem ultimately drives the analysis. I can code my own estimators, execute SQL queries, parse text files, and visualize a social network.